Digital signal processing (DSP) is the mathematical manipulation of a signal to modify or improve the signal. Generally, a continuous time analog signal is first converted to a discrete time digital representation of the signal via the widely known process of analog to digital (A/D) conversion. While DSP and A/D are well known concepts that are used in many applications, larger bandwidth signals can create problems. For example, a 1 MHz bandwidth signal generally requires a 2 MHz sampling rate to avoid aliasing. Each sample is represented digitally by some number of bits. With more bits comes better resolution and better signal-to-noise ratio (SNR) over quantization noise. So, if each sample in the 2 MHz sampling rate was represented by 8 bits, the bit rate of the sampled signal would 16 Megabits per second (Mbps). This bit rate is easily obtained with current state of the art processing. But, if the signal is a 100 MHz active Radio Frequency (RF) signal and the resolution is 16 bits, then the bit rate of the signal is 3.2 Gigabits per second (Gbps) without even considering the effects of additional data required for error correction in real time processing. These larger bandwidth signals require much faster bit rates that are simply too difficult to process in real time.